Gemini Computer Use vs Granite 4.2 30B

At a Glance

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Gemini Computer UseGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$1.25Google AI · Aug 29, 2026$0.16Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokens$10.00Google AI · Aug 29, 2026$0.65Deepinfra · Sep 22, 2026
Context windowMaximum documented tokens128K131K
Model facts checkedAug 29, 2026View model evidence →Sep 2, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldGemini Computer UseGranite 4.2 30B
DeveloperGoogle DeepMindIBM
FamilyGemini ToolsGranite 4 2
ModelGemini Computer UseGranite 4.2 30B
VersionGemini Computer UseGranite 4.2 30B
Lifecyclepreviewactive
ReleasedUnknown2026-08-25
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window128K131K
Total parametersUnknown29.3B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Deepinfra (Standard)
Capabilitiesgeneration, reasoning, toolschat, generation, reasoning, structured_outputs, tools

Gemini Computer Use Capabilities

generationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-2.5-computer-use-preview-10-2025

Granite 4.2 30B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDibm-granite/granite-4.2-30b

Primary Evidence

Sources and Freshness

Questions

Gemini Computer Use vs Granite 4.2 30B FAQs

Is Gemini Computer Use or Granite 4.2 30B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Computer Use and Granite 4.2 30B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini Computer Use or Granite 4.2 30B?+

Gemini Computer Use is $1.25 and Granite 4.2 30B is $0.16 per million tokens, so Granite 4.2 30B is cheaper on this metric. Gemini Computer Use is $10.00 and Granite 4.2 30B is $0.65 per million tokens, so Granite 4.2 30B is cheaper on this metric.

Which has a larger context window, Gemini Computer Use or Granite 4.2 30B?+

Granite 4.2 30B has the larger sourced context window. Gemini Computer Use supports 128K and Granite 4.2 30B supports 131K.

Which performs better in benchmarks, Gemini Computer Use or Granite 4.2 30B?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Gemini Computer Use or Granite 4.2 30B be self-hosted?+

Granite 4.2 30B is the only model in this pair currently marked as self-hostable. Gemini Computer Use is not marked open weight; Granite 4.2 30B is open weight.

Can Gemini Computer Use and Granite 4.2 30B understand images?+

Gemini Computer Use is documented with image input; Granite 4.2 30B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini Computer Use or Granite 4.2 30B?+

Neither has a larger sourced maximum output. Gemini Computer Use is 64K and Granite 4.2 30B is —.

Do Gemini Computer Use and Granite 4.2 30B support reasoning and tool use?+

Gemini Computer Use: reasoning, tool calling, and image input. Granite 4.2 30B: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini Computer Use or Granite 4.2 30B?+

Gemini Computer Use has 2 sourced provider routes; Granite 4.2 30B has 1, so Gemini Computer Use has broader tracked availability.

Which offers better value, Gemini Computer Use or Granite 4.2 30B?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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